How To Calculate Sample Size Using Power Analysis

Power matters!

Power analysis is used to estimate the approximate sample size in an experiment.

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Timestamps
00:00 Introduction
00:20 What is power?
01:56 What does power look like?
Null and alternative hypotheses
02:26 What does power look like?
Type I error (α)
02:58 What does power look like?
Type I error (α) and statistical significance
03:37 What does power look like?
Type II error (β) and power
04:22 What does power look like? Power = 80%
05:37 The critical value
06:05 Power analysis


About the video
As more and more funding bodies are asking for the actual power calculations and reviewers are using power, the importance of power analysis will only rise in importance. Watch as Dr. Anne Segonds-Pichon, a Biostatistician, and one of the instructors on the Graphpad Statistics Bootcamp series demonstrates how you can use power analysis can help you get a large enough sample size to detect the effect you are looking for, while avoiding unnecessarily large sample sizes that waste resources.

In this video you will learn
- What power analysis is and why it’s needed
- Type I and Type II errors and how they relate to power
- The five parameters that affect power

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Presented by Dr Anne Segonds-Pichon, Bio-Statistician from the Babraham Institute.
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